Conventional automated identification systems may in addition perform data collection functions. Such systems typically include tags, readers, and computer systems that perform application programs generally for monitoring the position and movement of tagged items, persons, and animals. These systems have wide utility in personal, commercial, government, education, and scientific fields including, for example, managing inventory (e.g., auto parts, mail, baggage), capturing point of sale transactions (e.g., groceries, utility meters), capturing product life cycle information (e.g., truck tires), controlling access to facilities and equipment by authorized persons, and monitoring the movements of vehicles, livestock, prisoners, soldiers, children, and employees, to name a few applications. Information and statistics from automated identification systems may support business decision making (e.g., throughput planning, insurance claims, valuation of a business, improvement of a supply chain).
Readers and computer systems coupled to the readers for performing application programs represent functionality installed at an investment cost that is generally returned over time by the value of the automated identification and data provided by the system. It is desirable to reuse this installed investment as additional applications for automated identification and/or data collection are discovered. One approach is to upgrade readers and computer systems to read additional types of tags and process additional types of information. Typically, upgrading software is less expensive than upgrading hardware.
Unfortunately, software for use in automated identification systems is difficult to design, deploy, and upgrade in part because determinations that are fundamental to system functions are generally made in the application program. For example, readers that report raw data to an application program place the burden of raw data analysis on the application program for an increasing quantity and perhaps decreasing quality of raw data as the number of readers in an installation increases. Raw data communication may also adversely consume the capacity of communication media including wired and wireless networks between readers and computer systems performing the application programs. The fundamental notion of the location of a tag is typically determined in the application program based on the identity of the tag, the identity of the reader reporting the tag, and the installed location of the reader. Another fundamental notion, to control equipment in the neighborhood of the tag, is conventionally accomplished by the application program. Consequently, there remains a need to reserve to the application program operating in an upper layer of the system those functions that are unique to the application (e.g., inventory replenishment thresholds) and to perform in a lower layer of the system functions that may be useful in one or more of several applications (e.g., reporting the location of a tagged item).
As automated identification systems expand to cover more items, it is desirable to be able to add equipment and software with a minimum of reconfiguration of existing equipment and software. It is also desirable to add diverse readers and diverse application programs with a minimum of reconfiguration of the existing investment as new applications in the same locations are identified. For example, an employer's system may initially control access to facilities by employees. Later the employer may desire to perform operations research and/or capital equipment utilization research. These additional applications may require diverse tags, diverse readers, and additional application program resources. It is desirable to make these additional application programs operable with a minimum of additional investment.
Without systems and methods according to various aspects of the present invention, the proliferation and integration of reliable and scalable automated identification and data collection systems will be impeded. Consequently, the costs of such systems will not reflect greater economies of scale. Benefits to the public will not be realized including material benefits of lower costs of goods (e.g., owing to less shrinkage), lower costs of services (e.g., package delivery), and other benefits (e.g., lower the risk of losses due to ineffective security).